Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, University of Utah, School of Medicine, 675 Arapeen Drive, Suite 205, Salt Lake City, UT, 84108, USA.
Division of Epidemiology, Study Design and Biostatistics Center, University of Utah Health Center for Clinical and Translational Science, 295 Chipeta Way, Salt Lake City, UT, 84122, USA.
J Assist Reprod Genet. 2020 May;37(5):1137-1145. doi: 10.1007/s10815-020-01731-8. Epub 2020 Mar 9.
To identify factors predictive of having supernumerary embryos in a fresh IVF cycle and create a prediction model for clinical counseling.
We utilized a multivariable Poisson regression to identify predictive factors and then entered these into a logistic regression model, calculating a risk index for each significant variable. The final model was tested using a receiver operating characteristic curve.
A total of 60,616 fresh transfer cycles were reported to the Society for Assisted Reproductive Technology in 2014. Of these, 47.17% produced supernumerary embryos. A multivariate Poisson regression identified factors predictive of having supernumerary embryos, with age and AMH being the most predictive. Clinical prediction models were developed with acceptable and excellent discrimination. 23.5% of our cohort did not achieve a live birth following their fresh transfer and had excess embryos cryopreserved for future attempts.
Our study suggests that in a minority of fresh IVF cycles in the USA, the fresh transfer is not successful, and there are excess embryos cryopreserved for future use. The likelihood of excess embryos beyond those that would be transferred can be predicted with satisfactory precision prior to initiation of the cycle and with improved precision after fresh embryo transfer. Providing patients with a realistic estimate of their chances of having excess embryos at an initial IVF consult especially those with suspected poor prognosis can be beneficial in determining whether to proceed with multiple embryo banking cycles as opposed to proceeding with a fresh transfer, and whether to opt for an enhanced embryo selection technique such as preimplantation genetic testing for aneuploidy (PGT-A).
确定新鲜体外受精（IVF）周期中出现多余胚胎的预测因素，并建立用于临床咨询的预测模型。
我们利用多变量泊松回归确定预测因素，然后将这些因素纳入逻辑回归模型，为每个显著变量计算风险指数。最后使用受试者工作特征曲线对最终模型进行测试。
2014 年，共有 60616 个新鲜胚胎移植周期向辅助生殖技术协会报告。其中，47.17%产生了多余胚胎。多变量泊松回归确定了产生多余胚胎的预测因素，年龄和 AMH 是最具预测性的因素。临床预测模型具有可接受和优秀的区分度。我们队列中有 23.5%的患者在新鲜胚胎移植后未实现活产，并冷冻保存了多余的胚胎以备未来尝试。
我们的研究表明，在美国少数新鲜 IVF 周期中，新鲜胚胎移植不成功，并且有多余的胚胎冷冻以备未来使用。在开始周期之前，可以用令人满意的精度预测超出可移植胚胎数量的多余胚胎的可能性，并且在新鲜胚胎移植后可以提高精度。在初始 IVF 咨询时，尤其是对那些预后不良的患者，向患者提供对其多余胚胎可能性的现实估计，特别是那些多余胚胎数量多的患者，这对确定是否进行多个胚胎储存周期或进行新鲜胚胎移植、以及是否选择增强胚胎选择技术（如植入前遗传学检测非整倍体[PGT-A]）非常有益。
